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1.
Nat Biotechnol ; 28(9): 935-42, 2010 Sep.
Article in English | MEDLINE | ID: mdl-20829833

ABSTRACT

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.


Subject(s)
Computational Biology/methods , Computational Biology/standards , Information Dissemination , Metabolic Networks and Pathways , Signal Transduction , Software , Databases as Topic , Programming Languages
2.
Genome Biol ; 8(3): R39, 2007.
Article in English | MEDLINE | ID: mdl-17367534

ABSTRACT

Reactome http://www.reactome.org, an online curated resource for human pathway data, provides infrastructure for computation across the biologic reaction network. We use Reactome to infer equivalent reactions in multiple nonhuman species, and present data on the reliability of these inferred reactions for the distantly related eukaryote Saccharomyces cerevisiae. Finally, we describe the use of Reactome both as a learning resource and as a computational tool to aid in the interpretation of microarrays and similar large-scale datasets.


Subject(s)
Computational Biology/methods , Knowledge Bases , Metabolic Networks and Pathways , Systems Biology , Animals , Databases as Topic , Humans , Internet , Microarray Analysis , Saccharomyces cerevisiae
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